4th International Conference On Building Energy, Environment

Comparative Computational Modeling of Airflow and Inhaled Particles Residence Times in the Human and Monkey Upper Respiratory Tracts

N.L. Phuong 1,2, N.D. Khoa 2, T.V. Quang 2 and K. Ito 1

1 Faculty of Engineering Sciences, Kyushu University, Japan 2 Faculty of Environment, Hochiminh City - University of Natural Resources and Environment, Vietnam

SUMMARY Computational fluid dynamics (CFD) models are useful for predicting the transportation of gas phase contaminants and suspended aerosols in the airway, and contribute to the identification of their transportation mechanism, which is dependent on the aerosol size, anatomy, physiology, and breathing patterns. We developed CFD models of the respiratory tracts of a monkey and human that included the airways from the nose or mouth to the trachea, to discuss the anatomical differences from a fluid dynamics/engineering perspective. Herein, the airflow and aerosol transportation were analyzed under steady-state inhalation conditions for direct comparisons with previously reported data and nasal-only simulations. Our results showed that the particle residence time was sensitive to the airway geometry, airflow rates, inflow boundary conditions, and particle size. Nasal removal efficiencies were predicted to be higher in the monkey model compared with the human model.

INTRODUCTION The nasal airways of rhesus monkeys and humans were considered similar in morphological structure (e.g., Desso, 1993). Because of such similarity, monkeys have been utilized instead of human to assess the toxic and therapeutic potential of inhaled substances (e.g., Petruska et al., 1997) and have been the focus of research on nasal clearance (Wolff et al., 1993). Replicas of rhesus monkey nasal airways have been used in airflow and particle deposition studies (Kelly et al., 2005). Data from particle inhalation studies using monkey and human airway models are expecting to provide better understanding of the nasal deposition of particles larger than 1 m in monkey and human.

In this study, CFD has been applied as the approach for developing an understanding of the air flow patterns, as well as particle transportation in a human and monkey respiratory tract (airway).

METHODS Anatomical Data Human: Respiratory tract data were obtained using a Toshiba 64 multi-detector row computed tomography (CT) scanner. The human participants were non-smoking European males of a standard body type and weight. The original set of CT images was converted into a file format compatible with Mimics® (Materialise NV). The generation of a surface model from the two-dimensional (2D) contour data was initiated by translating the segmented, modified, and smoothed contour points into a data series that was loaded into the ANSYS ICEM CFD and TGrid software. Both the packages were used to modify the surface mesh and then create a volume mesh of the model. In addition, the surface geometries of the respiratory tracts were exported in STL (stereolithography) format.

Monkey: CT imaging of the upper airways was performed on a 6-month-old, 1.2-kg male Macaca fascicularis monkey, from the nose/mouth through the trachea. The computational model was discretized and meshed using the ANSYS ICEM CFD software with unstructured tetrahedral elements. Table 1 presents the detailed geometric information for the two upper airway models. Figure 1 shows the structures of the obtained virtual airway models.

Table 1. Details of the monkey and human airway models

Monkey Human

Total inner surface area [m2]

2.81 × 10-5 2.14 × 10-4

Total length [m] 1.05 × 10-1 1.95 × 10-1

Maximum height [m] 4.32 × 10-2 1.34 × 10-1

Maximum width [m] 2.81 × 10-2 6.21 × 10-2

Total volume [m3] 5.59 × 10-5 1.27 × 10-5

Computer Simulations Airflow simulations: The simulation methods and conditions used to obtain the results in this study were implemented by

a) Monkey airway

b) Human airway

Figure 1. Monkey and human upper airway models

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4th International Conference On Building Energy, Environment

an approach similar to that reported by Phuong and Ito (2015). The flow of air in the nasal passages can be described via the Navier–Stokes equation and continuity equation, and by the imposition of appropriate boundary conditions. The steady flow fields were analyzed using the low-Reynolds number type k–ε model (Abe Kondo Nagano model). At normal physiological flow rates, incompressible flow conditions can be assumed. The fluid conditions were specified at the trachea opening, with the velocity defined to be constant in magnitude and perpendicular to the surface. The value of the turbulent kinetic energy at the inlet was prescribed assuming 10% turbulence intensity. On the solid surfaces, a no slip boundary condition was applied. A second order upwind scheme was used for the convection term, and the SIMPLE algorithm was employed. The centers of the computational cells closest to the wall surface were created to ensure a non-dimensional distance (wall unit) of y+ < 1.

Table 2. Numerical and boundary conditions

Monkey Human Turbulence Mode: Low-Reynolds Number Type k–ε model

Mesh

7.03 M mesh

(Unstructured,

Tetra)

3.81 M mesh

(Unstructured,

Tetra)

Outflow

boundary

(Trachea

opening)

Case 1: Q = 2.2

Case 2: Q = 3.5

Case 3: Q = 4.6

(L/min)

TI = 10%

kout = 3/2 (Uin 0.1)2

εout = Cµ

3/4kout

3/2lout

Case 1: Q = 7.5

Case 2: Q = 15

Case 3: Q = 30

(L/min)

TI = 10%

kout = 3/2 (Uin 0.1)2

εout = Cµ

3/4kout

3/2lout

Inflow boundary: Nasal opening Uin= k

in= ε

in= gradient

zero

Wall

treatment Velocity: no slip Velocity: no slip

CFD simulations were performed to calculate the airflow and particle residence time under various breathing conditions. Steady flow fields were analyzed using a low-Reynolds number type k—ε model, and the particle behaviors were computed using a Lagrangian discrete phase model. The simulations of particle tracking used flow rates of 7.5, 15, and 30 L/min; and 2.2, 3.5, and 4.9 L/min in the human and monkey airway, respectively. The simulations followed equation 1.

2

18p D p p

p S

p p p

du C Reu u g F

dt d 24

(1)

The left-hand side of equation 1 represents the inertial force. On the right-hand side, the first term is the drag force, the

second term represents the gravity and buoyancy, and SF

is

the Saffman’s lift force. A total of 10,000 particles (No) were distributed from both nostrils in each case. The behaviors of the dispersed particles of 1, 2.5, 5, 7.5, and 10 µm diameters were investigated in this study. The particle density was assumed to be 1000 kg/m3. The particles were defined by the injection file specifying the particle properties and position. This study used constant time step Δt = 1 × 10-6 (s).

RESULTS

Comparison between monkey and human airflow

A comparison of the results obtained from the monkey and human upper airway models can be made, owing to their similar anatomical structure. The nasal cavity of the rhesus monkey and human consisted of two airways separated by the septum wall.

The septum extended from the nostril plane of the soft palate in the nasopharynx. From the nasopharynx, the airway made a 90° bend toward the larynx. The flow patterns from the nostril down to the trachea are briefly described in Figure 2, to facilitate understanding of the physiology characteristics in the monkey and human upper airways. Figure 2 shows the airflow fields through the sagittal section in the monkey and human nasal cavities. Inlet angles can affect the air flows entering the different sections within their own cavity. In the monkey airway model, the flow in the nasal vestibule exhibited the highest velocity, and back flows occurred in this region. Schreck et al. (1993) considered the expansion to cause vortices in the human and monkey airway models.

The introduction of particles in the airflow involved a coupling of the secondary solid phase with the gas phase. Mono-dispersed particles were released uniformly in a direction normal to each nostril surface of the nasal cavity. Figure 3 displays the trajectories of 100 representative particles at the size fraction of 1 and 10 μm in the monkey upper airway. Fine particles (1 μm) follow curved streamlines at the flow rate of 3.5 L/min. It is clearly seen that from the vestibule region to

(1) Monkey airway

(2) Human airway

Figure 2. Numerical results of the human airway model: velocity profiles in the upper airway model at inspiratory flow rates of 3.5 L/min (Monkey airway) and 15 L/min (Human airway).

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4th International Conference On Building Energy, Environment

the anterior turbinate area, large airborne particles (10 μm) were the most highly retained in this study.

Figure 4 shows the trajectories of 100 representative particles at the size fraction between 1 and 10 μm in the human upper airway. 1-m particles tend to follow curved streamlines similar to the monkey upper airway. 10-m particles have been transported to distal region much higher amount than in monkey upper airway.

Figure 5 compares the normalization of the number of particles with their residence times (collected at the outlet of the trachea region) with the nominal time constant of fluid stream in all cases. was defined by the volume of the device [m3] divided by the inhaled air flow rate [m3/s]. In the monkey and human upper airways, the particles whose sizes were Dp =1 µm and Dp = 2.5 μm tend to follow the stream line of the gas streams and move out of the complex domain earlier than the particles with larger sizes at the point of nominal time constant . As particle size increases, the relaxation time that the particle needs to adapt to flow changes also increases. The large particles (Dp = 10 μm) are accelerated by the inertial force that tends to maintain the particles’ linear motion, while the airflow turns from the nostrils to the anterior turbinate, inducing an inertial impact on the wall surface. In this calculation, large particles (Dp = 10 µm) in the human upper airway tend to leave the airway much more than in the monkey airway when there is a nominal time constant. In contrast, upon attaining a nominal time constant, the number of large particles in the monkey upper airway is higher than in the human upper airway.

CONCLUSIONS

We have been built up 3D-models of human and monkey airway models to simulate flow field and particle movements with aerodynamic diameters from 1 to 10 µm at steady-state flow rates. The airflow pattern, trajectories and residence times of particles have been reported with various breathing rates. Particles of 1-10 m were terminated their trajectories in the upper vestibule region of monkey more than in human,

which suggests that monkey is likely more exposure in the nasal cavity. The results show that the trend of resident time of fine particle (1-2.5 m) in the monkey airways is leaving earlier that than in human airways with different breathing rates. These data may be used to understand the particle behaviors in the monkey and human nasal airways, and provide input data for the lower respiratory tract.

ACKNOWLEDGEMENT This project was supported by a Grant-in-Aid for Scientific Research (JSPS International Research Fellow).

REFERENCES Phuong, N. L. and Ito, K. 2015. “Investigation of flow pattern

in upper human airway including oral and nasal inhalation by PIV and CFD”. Build. Environ. 94, 504–515.

Ito, K., Mitsumune, K., Kuga, K., Phuong, N. L., Tani, K., and Inthavong, K., 2016. “Prediction of convective heat transfer coefficients for the upper respiratory tracts of rat, dog, monkey, and humans”. Indoor and Built Environment. 26:6, 828–840

Desso, J. M. 1993. The relevance to humans of animal models for inhalation studies of cancer in the nose and upper airways. Qual. Assur. 2(3):213–231

(a) 1 m

(b) 10 m

Figure 3. Particle trajectories of 100 representative particles at the inspiratory flow rate of 3.5 L/min

(a) 1 m

(a) 10 m

Figure 4. Particle trajectories of 100 representative particles at the inspiratory flow rate of 15 L/min

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Kelly, J. T., Asgharian, B., Kimbell, J. S., and Wong, B. A. 2004. Particle deposition in human nasal airway replicas manufactured by different methods. Part I: Inertial regime particles. Aerosol Sci. Technol. 38, 1063–1071.

Kelly, J. T., Asgharian, B., and Wong, B. A. 2005/ “Inertial Particle deposition in a monkey nasal mold compared with that in human nasal replicas”, Inhalation Toxicology, 17:14, 823–830.

Schreck, S., Sullivan, K. J., Ho, C. M., and Chang, H. K. 1993. “Correlations between flow resistance and geometry in a odel of the human nose”. J. Appl. Physiol. 75, 1767–1775.

Petruska, J. M., Beattie, J. G., Stuart, B. O., Pai, S., Walters, K. M.,Banks, C. M., Lulham, G. W., and Mirro, E. J. 1997.Cardiovasculareffects after inhalation of large doses ofalbuterol dry powder in rats,monkeys, and dogs: Aspecies comparison. Fundam. Appl. Toxicol. 40:52–62.

Wolff, R. K., Allen, D. L., Hughes, B. L., Osier, M., and Dorato, M. A. 1993. Nasal clearance in rhesus monkeys. JAerosol Med. 6(2):111–119

(a) Qin = 2.2 L/m (a) Qin = 7.5 L/m

(b) Qin = 3.5 L/m (b) Qin = 15 L/m

(c) Qin = 4.6 L/m (c) Qin = 30 L/m(1) Monkey upper airway (2) Human upper airway

Figure 5. Residence times of the particles in the monkey and human upper airways

0 0.1 0.2 0.3Time (s)

0

0.5

1

NE/N

0

Case 3. Residence time of particles in the ventilation device

s

0 0.1 0.2 0.3 0.4Time (s)

0

0.5

1

NE/N

0

nominal time constantDp=10 m

Dp=7.5 m

Dp=5 m

Dp=2.5 m

Dp=1 m

Case 3. Residence time of particles in the ventilation device

s

0 0.05 0.1 0.15 0.2Time (s)

0

0.5

1

NE/N

0

nominal time constantDp=10 m

Dp=7.5 m

Dp=5 m

Dp=2.5 m

Dp=1 m

Case 3. Residence time of particles in the ventilation device

s

0 0.05 0.1 0.15 0.2Time (s)

0

0.5

1

NE/N

0

nominal time constantDp=10 m

Dp=7.5 m

Dp=5 m

Dp=2.5 m

Dp=1 m

Case 3. Residence time of particles in the ventilation device

s

0 0.04 0.08 0.12 0.16Time (s)

0

0.5

1

NE/N

0

nominal time constantDp=10 m

Dp=7.5 m

Dp=5 m

Dp=2.5 m

Dp=1 m

Case 3. Residence time of particles in the ventilation device

s

0 0.02 0.04 0.06 0.08 0.1Time (s)

0

0.5

1

NE/N

0

nominal time constantDp=10 m

Dp=7.5 m

Dp=5 m

Dp=2.5 m

Dp=1 m

Case 3. Residence time of particles in the ventilation device

s

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